(1) Technical Field
The present invention relates to techniques for the surveillance of objects in images, and more specifically to systems that automatically detect and track vehicles for use in automotive safety.
(2) Discussion
Current computer vision techniques for vehicle detection and tracking require explicit parameter assumptions (such as lane locations, road curvature, lane widths, road color, etc.) and/or use computationally expensive approaches such as optical flow and feature-based clustering to identify and track vehicles. Systems that use explicit parameter assumptions suffer from excessive rigidity, as changes in scenery can severely degrade system performance. On the other hand, computationally expensive approaches are typically difficult to implement and expensive to deploy.
To overcome these limitations, a need exists in the art for a system that does not make any explicit assumptions regarding lane and/or road models and that does not need expensive computation.
The following references are provided as additional general information regarding the field of the invention.
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